E-Commerce Enterprise Supply Chain Financing Risk Assessment Based on Linked Data Mining and Edge Computing
Author(s) -
Qiao Qu,
Cheng Liu,
Xinzhong Bao
Publication year - 2021
Publication title -
mobile information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.346
H-Index - 34
eISSN - 1875-905X
pISSN - 1574-017X
DOI - 10.1155/2021/9938325
Subject(s) - supply chain , supply chain risk management , business , reputation , supply chain management , risk management , status quo , finance , industrial organization , risk analysis (engineering) , service management , marketing , economics , market economy , social science , sociology
In recent years, the rapid development of information technology has affected the way the world economy operates. The emergence of e-commerce has greatly shortened the time and space distance between economic participants and maximized the sharing of resources. However, the financial management and risk assessment capabilities of the existing supply are insufficient to adapt to the rapidly developing new environment. This article uses a combination of normative analysis and empirical analysis to analyze the status quo of the supply chain of small and medium e-commerce companies. First, this article establishes an evaluation framework for the supply chain of e-commerce companies based on edge computing. Second, according to the distribution of the supply chain, this article adds the member’s predetermined quota, reputation, execution time, and other indicators as parameters to establish a fuzzy neural network model. On this basis, combined with the price regression model, the pricing plan is evaluated. The results show that the financing risk obtained by this model differs very little from the actual risk. The above-mentioned model constructs an e-commerce enterprise supply chain financing risk management model that adapts to the environment of the new era.
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